Reasoning about fluid motion I: finding structures

Authors:
Kenneth Yip
Affiliations:
Department of Computer Science, Yale University, New Haven, CT
Venue:
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Year:
1995

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Abstract

With the increasing role of high performance computing in attacking complex physical problems, there is an urgent need for the development of advanced computational technology to provide scientists with high-level assistance in the analysis, interpretation, and modeling of a massive amount of quantitative data. A critical area where this need is quite evident is the problem of turbulence. The overall research goal is to develop a computational environment to help scientists efficiently make observations and conceptual models of turbulence data sets. This paper presents the progress of this project. My approach is based on two key ideas: (1) Local interactions and evolution of coherent objects like vortices enable high-level qualitative interpretation of turbulence data, and (2) Abstracting from the particular features of fluid dynamical reasoning, 1 propose five core operations - aggregation, classification, re-description, spatial inference, and configuration change - as part of a general theory of imagistic reasoning. A new vortex-finding algorithm is also presented.